This website uses cookies to deliver some of our products and services as well as for analytics and to provide you a more personalized experience. Click here to learn more. By continuing to use this site, you agree to our use of cookies. We've also updated our Privacy Notice. Click here to see what's new.

This website uses cookies to deliver some of our products and services as well as for analytics and to provide you a more personalized experience. Click here to learn more. By continuing to use this site, you agree to our use of cookies. We've also updated our Privacy Notice. Click here to see what's new.

About Optics & Photonics TopicsOSA Publishing developed the Optics and Photonics Topics to help organize its diverse content more accurately by topic area. This topic browser contains over 2400 terms and is organized in a three-level hierarchy. Read more.

Topics can be refined further in the search results. The Topic facet will reveal the high-level topics associated with the articles returned in the search results.

Abstract

Past studies of the effects of bit depth on OCT magnitude data concluded that 8 bits of digitizer resolution provided nearly the same image quality as a 14-bit digitizer. However, such studies did not assess the effects of bit depth on the accuracy of phase data. In this work, we show that the effects of bit depth on phase data and magnitude data can differ significantly. This finding has an important impact on the design of phase-resolved OCT systems, such as those measuring motion and the birefringence of samples, particularly as one begins to consider the tradeoff between bit depth and digitizer speed.

C. Copeland and A. K. Ellerbee, “The effects of different gold standards on the assessment of the accuracy of different resampling techniques for optical coherence tomography,” Proc. SPIE. 8225–8237 (2012).

2012 (1)

C. Copeland and A. K. Ellerbee, “The effects of different gold standards on the assessment of the accuracy of different resampling techniques for optical coherence tomography,” Proc. SPIE. 8225–8237 (2012).

Choma, M. A.

Copeland, C.

C. Copeland and A. K. Ellerbee, “The effects of different gold standards on the assessment of the accuracy of different resampling techniques for optical coherence tomography,” Proc. SPIE. 8225–8237 (2012).

Ellerbee, A. K.

C. Copeland and A. K. Ellerbee, “The effects of different gold standards on the assessment of the accuracy of different resampling techniques for optical coherence tomography,” Proc. SPIE. 8225–8237 (2012).

Proc. SPIE (2)

C. Copeland and A. K. Ellerbee, “The effects of different gold standards on the assessment of the accuracy of different resampling techniques for optical coherence tomography,” Proc. SPIE. 8225–8237 (2012).

Figures (8)

Fig. 1 Vector plot of the measured OCT data (z-domain). I = signal vector, N = noise vector, and Y = the resultant. Components of the noise vector in quadrature with the signal vector lead to error δθ in the measured phase compared to the actual phase θ.

Fig. 3 Behavior of a non-ideal (N + 1)-bit ADC. ne accounts for internal noise and thresholding errors of the ADC. Left: ideal (N + 1)-bit quantizer (i.e., a perfect rounding operation); the resulting ADC output has a resolution < N + 1 due to ADC imperfections described by ne. Right: the ideal quantizer can be replaced with an equivalent white-noise model in which QN is an uncorrelated additive noise.

Fig. 4 Demonstration of the two-step fractional requantizer from Fig. 2 to generate ENOBs of 3.2 (a and b) and 1.5 (c and d) bits from a 4-bit sinusoidal input sampled 32 times per period (gray). Simulated ADC signals appear in red. Step i (a and c): apply a pseudorandom noise sequence (blue) of the appropriate variance to the input to account for ADC non-idealities. Step ii (b and d): Quantize the resulting noisy sequence (red) to yield an output with the appropriate ENOB.

Fig. 5 Common-path OCT system used in this work. The sample comprised either a coverslip or a piezo-mounted mirror imaged from behind the coverslip. The reflectivity of the coverslip was changed by adding liquid droplets of varying refractive index.

Fig. 6 Displacement sensitivity vs ENOB for (a) glass-air, (b) glass-water, and (c) glass-gel interfaces. Error bars indicate one standard deviation of variation between trials. Theoretical curves are based on Eq. (7) and Eq. (9); the latter is clearly a better fit to the data. Experimental data and theoretical predictions converge with decreasing sample reflectivity or ENOB, as predicted. The arrows in (a)–(c) indicate the point at which the experimental sensitivity worsened by 3 dB. Note that plot axes differ to improve visibility of the data. The dotted black lines in (d) indicate the point at which SNR dropped by 1 dB relative to the SNR at 12 bits.

Fig. 7 1mm x 1mm views of the topography of a coverslip (CS) and neutral density filter (NDF) generated from phase using 12-bit, 8-bit, and 5-bit data. Due to the high reflectivity of the coverslip surface, quantization-induced phase noise is small, allowing accurate phase extraction even at very low bit-depths. Phase noise increases more rapidly with reduced ENOB when the reflectivity is lower, as for the NDF (the box shows an area of strong degradation with the arrow pointing to a ring that disappears in the 5-bit image). Note that scales are different in the top and bottom images.

Fig. 8 Displacement of a PZT driven at 100 Hz sinusoidal drive as calculated from 12-bit data. Fig. (b) shows the error in the displacement that would result if the waveform were instead generated using lower ENOBs (the waveform from 12-bit data is considered error-free and the waveforms from lower ENOBs are subtracted); the dashed horizontal lines show the RMS vibration noise (0.5 nm corresponds to 8% of the dynamic range). Except at very low bit depths, quantization noise is insignificant compared to vibration noise, since the sample reflectivity is large.